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Journal Club

Data Skeptic

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Journal Club

Journal Club

Data Skeptic

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About Us

Welcome to a brand new show from Data Skeptic entitled "Journal Club".Each episode will feature a regular panel and one revolving guest seat. The group will discuss a few topics related to data science and focus on one featured scholarly paper which is discussed in detail.

Latest Episodes

Deep Fakes in a Court Room, Mass COVID-19 Testing with Biosensors, and BLEURT

We are back with our regular panel this week! Starting off we have Lan who brings us the article "Biosensors May Hold the Key to Mass Coronavirus Testing." Which talks about tech startups beginning to develop chips that signal the presence of the coronavirus RNA, antibodies, and antigens. George brings us a blog post all about BLEURT, titled "BLEURT: Learning Robust Metrics for Text Generation." Last but not least, Kyle discusses the main paper this week! He brought us a paper discussing DeepFakes popping up in court rooms with the paper titled "Courts and Lawyers Struggles With Growing Prevalence of DeepFakes." All works will be linked in the show notes.

38 MIN6 d ago
Comments
Deep Fakes in a Court Room, Mass COVID-19 Testing with Biosensors, and BLEURT

Covid-19 Misinformation, GPT-3, and Movement Pruning

We're back with a special guest panelist Leonardo Apolonio! He brings us the main paper this week titled "Movement Pruning: Adaptive Sparsity by Fine-Tuning." George shows us a blog post discussing GPT-3. Lan introduces us to an article about misinformation related to Covid-19. Last but not least, Kyle also has a topic about Covid-19 addressing contact tracing apps!

41 MIN1 w ago
Comments
Covid-19 Misinformation, GPT-3, and Movement Pruning

Open Source AI for Everyone, Diagnosing Blindness and Histogram Reweighting

Another week, another episode! We are back again with our regular panelists. George brings us a clinical field study with an AI that is being used to diagnose blindness. Lan discusses the article titled "AI Infrastructure for Everyone, Now Open Sourced." Last but not least, Kyle brings us our paper for the week. He brings us the paper "Extending Machine Learning Classification Capabilities with Histogram Reweighting."

32 MIN2 w ago
Comments
Open Source AI for Everyone, Diagnosing Blindness and Histogram Reweighting

Chip Design, Teaching Google, and Fooling LIME and SHAP

This weeks episode we have the regular panel back together! George brought us the blog post from Google AI, "Chip Design with Deep Reinforcement Learning." Kyle brings us a news item from CNET, "How People with Down Syndrome are Improving Google Assistant." Lan brings us the paper this week! She discusses the paper "Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods." All works mentioned will be linked in the show notes.

32 MIN3 w ago
Comments
Chip Design, Teaching Google, and Fooling LIME and SHAP

Hateful Memes, Carbon Emissions, and Detecting Ear Infections with Neural Networks

This week on Journal Club we have another panelist! Jesus Rogel-Salazar joins us this week to discuss the paper Automatic Detection of Tympanic Membrane and Middle Ear Infection. Kyle talks about the relationship between Covid-19 and Carbon Emissions. George tells us about the new Hateful Memes Challenge from Facebook. Lan joins us to talk about Google's AI Explorables. All mentioned work can be found in the show notes.

44 MINJUN 11
Comments
Hateful Memes, Carbon Emissions, and Detecting Ear Infections with Neural Networks

Animal Olympics, Whatsapp, and Models for Healthcare

This week we have a guest joining us, Francisco J. Azuaje G! He brings us the paper "How to Develop Machine Learning Models for Healthcare." Lan discusses "Animal AI Olympics," a reinforcement learning competition inspired by animal cognition. Kyle talks about WhatsApp and discusses the article "Why New Contact Tracing Apps Have A Critical WhatsApp-Sized Problem." Last but not least: George! He brings us his blog post about comparing TF-IDF and BERT vectorisation for speaker prediction. All works discussed can be found in the show notes.

41 MINJUN 4
Comments
Animal Olympics, Whatsapp, and Models for Healthcare

Deeply Tough Framework, Grammar for Agents, and Too Much Screen Time?

Today on the show Kyle discusses research which suggests that time on screens has little impact on kids' social skills.Lan talks about DeeplyTougha deep learning framework targeting the protein pocket matching problem - try to answer whether a pair of protein pockets can bind to the same ligand.George's paper this week is about defining a grammar for interpretable agents. By basing this formalism on a corpus of human explanation dialogues the authors hope to produce a more "grounded" protocol.

34 MINMAY 27
Comments
Deeply Tough Framework, Grammar for Agents, and Too Much Screen Time?

Chemical Space, AI Microscope, and Panda or Gibbon?

George talks about OpenAI's Microscope, a collection of visualisations of the neurons and layers in 6 famous vision models. This library hopes to make analysis of these models a community effort. Lan talks about Exploring chemical space with AI and how that may change pharmaceutical drug discovery and development. Kyle leads a discussion about the paper "Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions" which shows another control that an adversarial attacker can put in place to better fool machine learning models.

31 MINMAY 19
Comments
Chemical Space, AI Microscope, and Panda or Gibbon?

Encryption Keys, Connect Four, and Data Nutrition Labels

Today George takes inspiration and the gym environment from Kaggle's ConnectX competition and shows off and attempt to design an interpretable Connect 4 Agent with DQN! Lan discusses the paper "The Dataset Nutrition Label," which is a framework to facilitate higher data quality standards by Sarah Holland and co-authors, from the Assembly program at the Berkman Klein Center at Harvard University & MIT Media Lab. Last but not least, Kyles leads the panel in a discussion about encryption keys! Lan discusses Dataset nutrition Label Kyle discusses encryption keys

41 MINMAY 14
Comments
Encryption Keys, Connect Four, and Data Nutrition Labels

ML Cancer Diagnosis, Robot Assistants, and Watermarking Data

Today George talks about the use of Machine Learning to diagnose Cancer from a blood test. By sampling 'cell-free-DNA' this test is capable of identifying 50 different types of Cancer and the localized tissue of origin witha >90% accuracy. Lan leads a discussion of what robots and researchers in robotics may be able to contribute towardsfighting the COVID-19 pandemic. Last but not least, Kyle leads the panel in a discussion about watermarking data!

31 MINMAY 7
Comments
ML Cancer Diagnosis, Robot Assistants, and Watermarking Data

Latest Episodes

Deep Fakes in a Court Room, Mass COVID-19 Testing with Biosensors, and BLEURT

We are back with our regular panel this week! Starting off we have Lan who brings us the article "Biosensors May Hold the Key to Mass Coronavirus Testing." Which talks about tech startups beginning to develop chips that signal the presence of the coronavirus RNA, antibodies, and antigens. George brings us a blog post all about BLEURT, titled "BLEURT: Learning Robust Metrics for Text Generation." Last but not least, Kyle discusses the main paper this week! He brought us a paper discussing DeepFakes popping up in court rooms with the paper titled "Courts and Lawyers Struggles With Growing Prevalence of DeepFakes." All works will be linked in the show notes.

38 MIN6 d ago
Comments
Deep Fakes in a Court Room, Mass COVID-19 Testing with Biosensors, and BLEURT

Covid-19 Misinformation, GPT-3, and Movement Pruning

We're back with a special guest panelist Leonardo Apolonio! He brings us the main paper this week titled "Movement Pruning: Adaptive Sparsity by Fine-Tuning." George shows us a blog post discussing GPT-3. Lan introduces us to an article about misinformation related to Covid-19. Last but not least, Kyle also has a topic about Covid-19 addressing contact tracing apps!

41 MIN1 w ago
Comments
Covid-19 Misinformation, GPT-3, and Movement Pruning

Open Source AI for Everyone, Diagnosing Blindness and Histogram Reweighting

Another week, another episode! We are back again with our regular panelists. George brings us a clinical field study with an AI that is being used to diagnose blindness. Lan discusses the article titled "AI Infrastructure for Everyone, Now Open Sourced." Last but not least, Kyle brings us our paper for the week. He brings us the paper "Extending Machine Learning Classification Capabilities with Histogram Reweighting."

32 MIN2 w ago
Comments
Open Source AI for Everyone, Diagnosing Blindness and Histogram Reweighting

Chip Design, Teaching Google, and Fooling LIME and SHAP

This weeks episode we have the regular panel back together! George brought us the blog post from Google AI, "Chip Design with Deep Reinforcement Learning." Kyle brings us a news item from CNET, "How People with Down Syndrome are Improving Google Assistant." Lan brings us the paper this week! She discusses the paper "Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods." All works mentioned will be linked in the show notes.

32 MIN3 w ago
Comments
Chip Design, Teaching Google, and Fooling LIME and SHAP

Hateful Memes, Carbon Emissions, and Detecting Ear Infections with Neural Networks

This week on Journal Club we have another panelist! Jesus Rogel-Salazar joins us this week to discuss the paper Automatic Detection of Tympanic Membrane and Middle Ear Infection. Kyle talks about the relationship between Covid-19 and Carbon Emissions. George tells us about the new Hateful Memes Challenge from Facebook. Lan joins us to talk about Google's AI Explorables. All mentioned work can be found in the show notes.

44 MINJUN 11
Comments
Hateful Memes, Carbon Emissions, and Detecting Ear Infections with Neural Networks

Animal Olympics, Whatsapp, and Models for Healthcare

This week we have a guest joining us, Francisco J. Azuaje G! He brings us the paper "How to Develop Machine Learning Models for Healthcare." Lan discusses "Animal AI Olympics," a reinforcement learning competition inspired by animal cognition. Kyle talks about WhatsApp and discusses the article "Why New Contact Tracing Apps Have A Critical WhatsApp-Sized Problem." Last but not least: George! He brings us his blog post about comparing TF-IDF and BERT vectorisation for speaker prediction. All works discussed can be found in the show notes.

41 MINJUN 4
Comments
Animal Olympics, Whatsapp, and Models for Healthcare

Deeply Tough Framework, Grammar for Agents, and Too Much Screen Time?

Today on the show Kyle discusses research which suggests that time on screens has little impact on kids' social skills.Lan talks about DeeplyTougha deep learning framework targeting the protein pocket matching problem - try to answer whether a pair of protein pockets can bind to the same ligand.George's paper this week is about defining a grammar for interpretable agents. By basing this formalism on a corpus of human explanation dialogues the authors hope to produce a more "grounded" protocol.

34 MINMAY 27
Comments
Deeply Tough Framework, Grammar for Agents, and Too Much Screen Time?

Chemical Space, AI Microscope, and Panda or Gibbon?

George talks about OpenAI's Microscope, a collection of visualisations of the neurons and layers in 6 famous vision models. This library hopes to make analysis of these models a community effort. Lan talks about Exploring chemical space with AI and how that may change pharmaceutical drug discovery and development. Kyle leads a discussion about the paper "Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions" which shows another control that an adversarial attacker can put in place to better fool machine learning models.

31 MINMAY 19
Comments
Chemical Space, AI Microscope, and Panda or Gibbon?

Encryption Keys, Connect Four, and Data Nutrition Labels

Today George takes inspiration and the gym environment from Kaggle's ConnectX competition and shows off and attempt to design an interpretable Connect 4 Agent with DQN! Lan discusses the paper "The Dataset Nutrition Label," which is a framework to facilitate higher data quality standards by Sarah Holland and co-authors, from the Assembly program at the Berkman Klein Center at Harvard University & MIT Media Lab. Last but not least, Kyles leads the panel in a discussion about encryption keys! Lan discusses Dataset nutrition Label Kyle discusses encryption keys

41 MINMAY 14
Comments
Encryption Keys, Connect Four, and Data Nutrition Labels

ML Cancer Diagnosis, Robot Assistants, and Watermarking Data

Today George talks about the use of Machine Learning to diagnose Cancer from a blood test. By sampling 'cell-free-DNA' this test is capable of identifying 50 different types of Cancer and the localized tissue of origin witha >90% accuracy. Lan leads a discussion of what robots and researchers in robotics may be able to contribute towardsfighting the COVID-19 pandemic. Last but not least, Kyle leads the panel in a discussion about watermarking data!

31 MINMAY 7
Comments
ML Cancer Diagnosis, Robot Assistants, and Watermarking Data
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